Showing 2 results for Shahbazi
- Ghazale Rafiee, - Aida Maleki, - Yaser Shahbazi, Asghar Molaei,
Volume 11, Issue 3 (12-2024)
Abstract
Natural biological crises are a constant threat to human societies; Therefore, it is considered important to be prepared to control and prevent such disasters. In dealing with such urban crises, addressing the category of non-pharmacological interventions against infectious diseases can be a way forward. Therefore, the aim of the current research is to find the main effective indicators in the epidemic and to explain the environmental components resulting from the interaction and correlation of the relevant measurable indicators at the locality level based on previous environmental studies.
In this research, in order to obtain a community of opinion about effective indicators in epidemiological crises, a systematic search was first conducted using the keyword of pandemic resilience. For this purpose, several widely used databases such as Web of Science, Scopus and Elsevier were searched between 2013 and 2023. After checking the quality of the conducted researches, 42 indicators were selected. Further, in order to find out the underlying variables and identify the basic factors or criteria in order to explain the correlation pattern between the observed variables, the exploratory factor analysis method was used and SPSS version 26 software was used to analyze the data. Data from 118 Tabriz neighborhoods were used for exploratory factor analysis. After collecting the data, the process of change, standardization has been done to prepare the data and convert the raw data into percentage, growth rate, average and ratio. Then, the status of urban resilience components against epidemic diseases was calculated and normalized separately based on factor load for each neighborhood. Finally, the results were illustrated using Arc GIS software.
The findings of the research indicate that 42 indicators affecting the spread of epidemic diseases at the level of localities can be re-categorized into 8 components of accumulation, diversity and design, social factors, density, economic factors, health infrastructure, environmental pollution and green spaces. Also, based on the findings, it can be said that the condition of most of the components in the neighborhoods of Tabriz city is at an average level.
Based on the results, the effects of environmental factors on the transmission of Covid-19 are differentiated spatially. These components represent more than 82% of the changes in effective environmental factors.
Dr Sayyad Asghari Sarasekanrood, Zahra Sharifi, Zahra Shahbazi,
Volume 11, Issue 4 (2-2025)
Abstract
Landslides, as one of the most dangerous natural hazards in mountainous regions, continuously threaten human infrastructure, especially roads and transportation routes. Their occurrence often results in significant loss of life and property, making it crucial to study and assess landslide hazards for effective zoning. The purpose of this research is to zone the landslide hazard along the Masal to Gilvan road using a neural network algorithm. The neural network algorithm is recognized as one of the most effective machine learning models, capable of solving complex problems in prediction and classification despite its simplicity. For this zoning analysis, nine influencing factors were considered: (1) geology, (2) vegetation cover, (3) slope, (4) land use, (5) distance from the road, (6) slope aspect, (7) elevation, (8) distance from fault lines, and (9) distance from rivers. The data were prepared, preprocessed, and then entered into MATLAB 2018. A neural network model was designed and implemented with 9 input neurons, 8 hidden neurons, and 1 output neuron. The results indicated that the four most influential factors, ranked by weight, were: slope (0.24), vegetation cover (0.17), distance from fault lines (0.14), and geology (0.11). Final validation using the ROC curve showed that the AUC values were 0.854 for the training phase and 0.971 for the testing phase, both of which reflect highly favorable results. The error rate was found to be very low.
